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Multimodal Learning For Classroom Activity Detection

Classroom activity detection (CAD) focuses on accurately classifying whether the teacher or student is speaking and recording both the length of individual utterances during a class. A CAD solution helps teachers get instant feedback on their pedagogical instructions. This greatly improves educators' teaching skills and hence leads to students' achievement. However, CAD is very challenging because (1) the CAD model needs to be generalized well enough for different teachers and students; (2) data from both vocal and language modalities has to be wisely fused so that they can be complementary; and (3) the solution shouldn't heavily rely on additional recording device. In this paper, we address the above challenges by using a novel attention based neural framework. Our framework not only extracts both speech and language information, but utilizes attention mechanism to capture long-term semantic dependence. Our framework is device-free and is able to take any classroom recording as input. The proposed CAD learning framework is evaluated in two real-world education applications. The experimental results demonstrate the benefits of our approach on learning attention based neural network from classroom data with different modalities, and show our approach is able to outperform state-of-the-art baselines in terms of various evaluation metrics.Comment: The 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020

Human Motion Transfer with 3D Constraints and Detail Enhancement

We propose a new method for realistic human motion transfer using a generative adversarial network (GAN), which generates a motion video of a target character imitating actions of a source character, while maintaining high authenticity of the generated results. We tackle the problem by decoupling and recombining the posture information and appearance information of both the source and target characters. The innovation of our approach lies in the use of the projection of a reconstructed 3D human model as the condition of GAN to better maintain the structural integrity of transfer results in different poses. We further introduce a detail enhancement net to enhance the details of transfer results by exploiting the details in real source frames. Extensive experiments show that our approach yields better results both qualitatively and quantitatively than the state-of-the-art methods

Construction of a nomogram for preoperative prediction of the risk of lymph node metastasis in early gastric cancer

BackgroundThe status of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) is particularly important for the formulation of clinical treatment. The purpose of this study was to construct a nomogram to predict the risk of LNM in EGC before operation.MethodsUnivariate analysis and logistic regression analysis were used to determine the independent risk factors for LNM. The independent risk factors were included in the nomogram, and the prediction accuracy, discriminant ability and clinical practicability of the nomogram were evaluated by the receiver operating characteristic curve (ROC), calibration curve and clinical decision curve (DCA), and 100 times ten-fold cross-validation was used for internal validation.Results33 (11.3%) cases of AGC were pathologically confirmed as LNM. In multivariate analysis, T stage, presence of enlarged lymph nodes on CT examination, carbohydrate antigen 199 (CA199), undifferentiated histological type and systemic inflammatory response index (SIRI) were risk factors for LNM. The area under the ROC curve of the nomogram was 0.86, the average area under the ROC curve of the 100-fold ten-fold cross-validation was 0.85, and the P value of the Hosmer-Lemeshow test was 0.60. In addition, the clinical decision curve, net reclassification index (NRI) and Integrated Discriminant Improvement Index (IDI) showed that the nomogram had good clinical utility.ConclusionsWe found that SIRI is a novel biomarker for preoperative prediction of LNM in EGC, and constructed a nomogram for preoperative prediction of the risk of LNM in EGC, which is helpful for the formulation of the clinical treatment strategies

Three low-mass companions around aged stars discovered by TESS

We report the discovery of three transiting low-mass companions to aged stars: a brown dwarf (TOI-2336b) and two objects near the hydrogen burning mass limit (TOI-1608b and TOI-2521b). These three systems were first identified using data from the Transiting Exoplanet Survey Satellite (TESS). TOI-2336b has a radius of $1.05\pm 0.04\ R_J$, a mass of $69.9\pm 2.3\ M_J$ and an orbital period of 7.71 days. TOI-1608b has a radius of $1.21\pm 0.06\ R_J$, a mass of $90.7\pm 3.7\ M_J$ and an orbital period of 2.47 days. TOI-2521b has a radius of $1.01\pm 0.04\ R_J$, a mass of $77.5\pm 3.3\ M_J$ and an orbital period of 5.56 days. We found all these low-mass companions are inflated. We fitted a relation between radius, mass and incident flux using the sample of known transiting brown dwarfs and low-mass M dwarfs. We found a positive correlation between the flux and the radius for brown dwarfs and for low-mass stars that is weaker than the correlation observed for giant planets.Comment: 20 pages, 13 figures; submitted to MNRA

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

Experimental and Numerical Study on the Effect of Hydrogen Addition on Laminar Burning Velocity of Ethanol–Air Mixtures

To understand the effect of hydrogen addition on the laminar burning velocity (LBV) of ethanol–air mixtures, experiments were conducted in a constant volume combustion chamber with the high-speed schlieren photography technique. The experiments were carried out under the equivalence ratios (ERs) of 0.7–1.4, an initial temperature of 400 K, an initial pressure of 0.1 MPa, and hydrogen fractions of 30% and 90% by volume, respectively. The effects of ER, initial temperature, initial pressure, and hydrogen fractions on the LBV were investigated. Moreover, adiabatic flame temperature (AFT), heat release rate (HRR), flow rate sensitivity analysis, and ROP (rate of production) analysis were also performed. Results showed that LBV increased with increasing hydrogen addition and temperature but decreased with increasing pressure. The hydrogen addition significantly increased the HRR of ethanol–hydrogen–air flames. The sensitivity analysis showed that R5 (O2 + H = O + OH) significantly influenced the LBV

Thermal Conductivity of Silica-aerogel (SA) and Autoclave Aerated Concrete (AAC) Composites

Improving the thermal insulating performance of porous building materials is of great practical significance for building energy conservation. In this work, silica aerogels (SA) with ultralow thermal conductivity were proposed as an appropriate candidate to be integrated with autoclaved aerated concrete (AAC) to produce novel SA-AAC composites with higher thermal insulating performance by physical solution impregnation method. The pore-structures, mechanical and thermal properties of the SA-AAC composites were probed by various experimental tests. According to the microscopy and porosimetry results, SA were observed to adhere to the surface walls of the AAC holes, thus reducing the amount of macro-sized pores. In addition, the improved thermal insulating performance of AAC was successfully achieved with the relative improvement depending on the porosity of the pristine AAC. At the mass fraction of SA of ~7%, the highest relative improvement was found to be ~30% The results of this work exhibited a great potential of this novel SA-AAC composite in engineering applications

Effect of ethanol fumigation on pericarp browning associated with phenol metabolism, storage quality, and antioxidant systems of wampee fruit during cold storage

Abstract Wampee fruit is a popular fruit cultivar in South‐East Asia due to its high levels of nutrients and antioxidants; however, pericarp browning leads to a short storage life with great economic loss during years. The purpose of this work was to determine whether postharvest ethanol fumigation affected pericarp browning development of wampee fruit during 12 days of storage at 8 ± 0.5°C, and if so, how it is related to phenol metabolism and how it affects quality attributes and antioxidant systems during storage. After fruits were fumigated with 100, 300, 500, and 800 μl/L for 5 hr at 22 ± 0.5°C, ethanol significantly reduced the development of pericarp browning by increasing total phenolics (TP) content and decreasing the activity of polyphenol oxidase (PPO), especially in 500 μl/L ethanol treatment. Additionally, ethanol delayed the losses in fruit firmness (FF), soluble solid content (SSC), and titratable acidity (TA), retarded weight loss and accumulation of malondialdehyde (MDA) content and maintained relatively high contents of ascorbic acid (AsA), total flavonoids (TF), and total antioxidant capacity (TAC) and activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD). In conclusion, results demonstrated that postharvest ethanol fumigation in wampee fruit has ability to reduce pericarp browning development by regulating phenol metabolism and enhancing antioxidant systems

Sensitive chemical potential sensor based on graphene hyperbolic metamaterials

We have studied the anisotropic dispersion properties of hyperbolic metamaterials having a graphene/dielectric periodic structure and proposed a sensitive chemical potential sensor. It is found that the equifrequency contour of the structure will transit from an ellipse to a hyperbola as the chemical potential of graphene increases over a certain critical value. Interestingly, as the chemical potential increases close to the critical value, the transmittance varies very sensitively and nearly linearly in a wide range but with a small change of chemical potential. Based on these unique properties, we design a sensitive chemical potential sensor with advantages of fast response and high sensitivity simultaneously. Additionally, the measurement range of chemical potential can be expanded by adjusting the working frequency conveniently. These results have potential in many application fields such as beam control and sensing